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Inspired by the advanced integrated sensing and communication (ISAC), in this Letter, we explore the non-line-of-sight (NLoS) optical channels formed by reflections from the ground or objects to establish an integrated channel model for simultaneous communication and sensing. The integrated channel model can, on the one hand, perceive the changes in the surrounding environment and, on the other hand, determine whether these changes positively or negatively affect the quality of communication simultaneously. To validate the effectiveness of the proposed model, from sensing, we analyze the impact of various floor materials and visible light communication (VLC) users on the integrated channel; from communication, we characterize the influence of perceived environmental changes on communication performance by calculating throughput. Experimental results confirm the capability of the derived model, which can support the design and deployment of VL-based ISAC networks.
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Optical camera communication (OCC), enabled by light-emitting diodes (LEDs) and embedded cameras on smartphones, has drawn considerable attention thanks to the pervasive adoption of LED lighting and mobile devices. However, most existing studies do not consider the performance bottleneck of Region of Interest (RoI) extraction during decoding, making it challenging to improve communication capacity further. To this end, we propose a fast grid virtual division scheme based on pixel grayscale values, which extracts RoI quickly without sacrificing computational complexity, thereby reducing the decoding delay and improving the communication capacity of OCC. Essentially, the proposed scheme uses a grid division strategy to divide the received image into blocks and randomly sample several pixels within different blocks to quickly locate the RoI with high grayscale values in the original image. By implementing the lightweight RoI extraction algorithm, we experimentally verify its effectiveness in reducing decoding latency, demonstrating its superior performance in terms of communication capacity. The experimental results clearly show that the decoding delay of the proposed scheme is 70% lower than that provided by the Gaussian blur scheme for the iPhone receiver at a transmission frequency of 5 kHz.
Assuntos
Algoritmos , Iluminação , Sistemas Computacionais , ComunicaçãoRESUMO
As an important branch of visible light communication (VLC), optical camera communication (OCC) has received increasing attention recently, owing to its availability and low cost of deployment by re-using cameras as VLC receivers. However, cameras on popular smartphones and/or closed-circuit television systems have their primary function for taking pictures and recognizing objects, where the recorded images with objects are inevitable to be distorted by the coded light under OCC. To this end, we propose and experimentally demonstrate an improved OCC system which is able to achieve data communication and object recognition simultaneously. Basically, we devise an image restoration (IR) scheme to repair the pixels damaged by modulated light during data transmission, and it hence provides better image input to realize object recognition. Moreover, to maintain a reasonable data rate of OCC, we also engineer an object avoidance (OA) scheme to remove the negative effect caused by the object background in OCC frame. Finally, we implement a prototype of the proposed system to verify its performance on object recognition and communication, and experimental results show that the proposed IR can bring an improvement over 37% in terms of object recognition accuracy comparing to the baseline under a data rate of 5 kbps.
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Deemed as a practical approach to realize Visible Light Communication on commercial-off-the-shelf devices, the Optical Camera Communication (OCC) is attracting increasing attention, thanks to its readiness to be built purely upon ubiquitous LED illuminating infrastructure and handy smartphones. However, limited by the low sampling ability of the built-in camera on a smartphone, the performance of existing OCC systems is still far away from the requirements of practical applications. To this end, we further investigate the reception ability of the smartphone's camera and propose an accumulative sampling scheme to improve the performance of the OCC system. Essentially, the proposed scheme can use all the grayscale information of the pixels projected by the LED transmitter, whereas the conventional ones normally use single row (or column) pixels for demodulating. By implementing the lightweight demodulation algorithm with accumulative sampling, we experimentally verify its effectiveness for supporting higher transmission frequency hence better performance in terms of data rate. Extensive evaluations have shown the BERs of the proposed method are over 87% and 96% lower than that provided by the baselines at a maximum transmission frequency of 5 kHz for the Samsung S8 and iPhone 8 Plus receivers, respectively.
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Total knee arthroplasty has become one of the effective operation methods on end-stage knee osteoarthritis. However,the postoperative pain has been plaguing the clinicians. The cause of postoperative pain can be divided into iatrogenic, prosthesis and patient. Pain treatment in perioperative period includes preoperative education, analgesia in advance, and the selection and design of reinforcement; during operation mainly includes the appropriate surgical approach, keep the balance of soft tissue around the knee joint, cocktail analgesia pain around the knee joint; after operation mainly includes oral analgesic drugs, femoral nerve tissue and patient controlled analgesia. And the multimodal analgesi.a which is the analgesic methods combined application in perioperative period raised in resent years fully intervene the pain in perioperative period,so that it can effectively reduce the pain of patients after knee replacement, promote the patients do functional exercise more better and get better operation result.